What is the two phase method used for?

In Two Phase Method, the whole procedure of solving a linear programming problem (LPP) involving artificial variables is divided into two phases. In phase I, we form a new objective function by assigning zero to every original variable (including slack and surplus variables) and -1 to each of the artificial variables.

What are the advantages of two phase method?

To put it simply, the main advantage of the two-phase Simplex method is: in LP problems with equality in their constraints, and >= constraints (which usually occurs in a minimization problem), we need to use big M cost coefficient in the objective function for introduction of artificial variables.

What are the applications of LPP?

LPP applications may include production scheduling, inventory policies, investment portfolio, allocation of advertising budget, construction of warehouses, etc. In this article, we would focus on the different components of the output generated by Microsoft excel while solving a basic LPP model.

What is the 2 phase simplex method?

The two-phase method, as it is called, divides the process into two phases. Phase 1: The goal is to find a BFS for the original LP. Indeed, we will ignore the original objective for a while, and instead try to minimize the sum of all artificial variable.

What is the difference between Big M method and two phase method?

Step-by-step explanation: Big M method for finding the solution for a linear problem with simplex method. And in two phase method the whole procedure of solving a linear progamming problem (LPP) involving artificial veriables is divided into two phases.

Why do we use Big M method?

When used in the objective function, the Big M method sometimes refers to formulations of linear optimization problems in which violations of a constraint or set of constraints are associated with a large positive penalty constant, M. (hence the need for M to be “large enough.”)